✨ From vibe coding to vibe deployment. UBOS MCP turns ideas into infra with one message.

Learn more

Model Context Protocol (MCP) Python Implementation

This project implements a functioning Model Context Protocol (MCP) server and client in Python, following the Anthropic MCP specification. It demonstrates the key patterns of the MCP protocol through a simple, interactive example.

What is MCP?

The Model Context Protocol (MCP) is an open standard built on JSON-RPC 2.0 for connecting AI models to external data sources and tools. It defines a client-server architecture where an AI application communicates with one or more MCP servers, each exposing capabilities such as:

  • Tools: Executable functions that perform actions
  • Resources: Data sources that provide information
  • Prompts: Predefined templates or workflows

MCP standardizes how these capabilities are discovered and invoked, serving as a “USB-C for AI” that allows models to interact with external systems in a structured way.

Project Structure

  • server/: MCP server implementation
    • server.py: WebSocket server that handles MCP requests and provides sample tools/resources
  • client/: MCP client implementation
    • client.py: Demo client that connects to the server and exercises all MCP capabilities

Features Demonstrated

This implementation showcases the core MCP protocol flow:

  1. Capability Negotiation: Client-server handshake via initialize
  2. Capability Discovery: Listing available tools and resources
  3. Tool Invocation: Calling the add_numbers tool with parameters
  4. Resource Access: Reading text content from a resource

Setup

  1. Create a virtual environment:

    python3 -m venv .venv
    source .venv/bin/activate
    
  2. Install dependencies:

    pip install -r requirements.txt
    

Usage

  1. Start the MCP server (in one terminal):

    python server/server.py
    
  2. Run the MCP client (in another terminal):

    python client/client.py
    

The client will connect to the server, perform the MCP handshake, discover capabilities, and demonstrate invoking tools and accessing resources with formatted output.

How It Works

MCP Server

The server:

  • Accepts WebSocket connections
  • Responds to JSON-RPC requests following the MCP specification
  • Provides a sample tool (add_numbers)
  • Provides a sample resource (example.txt)
  • Supports the MCP handshake and capability discovery

MCP Client

The client:

  • Connects to the server via WebSocket
  • Performs the MCP handshake
  • Discovers available tools and resources
  • Demonstrates calling a tool and reading a resource
  • Presents the results in a formatted display

Protocol Details

MCP implements these key methods:

MethodDescription
initializeHandshake to establish capabilities
tools/listList available tools
tools/callCall a tool with arguments
resources/listList available resources
resources/readRead resource content
prompts/listList available prompts

Extending the Project

You can extend this implementation by:

  • Adding more tools with different capabilities
  • Adding dynamic resources that change on each read
  • Implementing prompt templates for guided interactions
  • Creating more interactive client applications

References

  • Anthropic Model Context Protocol Spec
  • JSON-RPC 2.0 Specification
  • WebSockets Protocol

Featured Templates

View More
Customer service
Service ERP
126 1188
AI Assistants
AI Chatbot Starter Kit v0.1
140 912
Verified Icon
AI Assistants
Speech to Text
137 1881
AI Characters
Sarcastic AI Chat Bot
129 1712

Start your free trial

Build your solution today. No credit card required.

Sign In

Register

Reset Password

Please enter your username or email address, you will receive a link to create a new password via email.